A Risk Assessment Method for Civil Aviation Passengers Based on The Fusion of Multi-risk Factors

Civil aviation passengers are the main implementers of civil aviation security measures. Therefore, in order to accurately assess the risk level of civil aviation passengers, a civil aviation passenger risk assessment method based on the fusion of multi-risk factors is proposed. The risk factors associated with passengers are identified through statistical analysis, regulation and expert investigation. According to the characteristics, the risk factors associated with passengers are categorized into three main parts: possibility, hazard and severity. Combined with the control measures, a risk index system for civil aviation passengers based on multi-risk factors is constructed, which contains 7 first-level indicators and 18 second-level indicators. The interval analytic hierarchy process can fully account for the uncertainty and fuzziness of expert judgments, while the set value statistics method allows for the quantitative representation of fuzzy indicators. By combining the advantages of these two methods, a quantitative analysis method based on the combination of internal analytic hierarchy process and set value statistics method are applied to calculate the weight coefficients of the risk indicators. To meet practical application requirements, passenger security data are collected throughout the passenger journey. And a risk assessment method for civil aviation passengers, based on the fusion of multi-risk factors, is proposed to enable dynamic quantitative risk assessments throughout the entire process. The proposed method is validated using a constructed validation dataset. The experimental results show that the recall rate for high-risk passengers reached 92%, with no high-risk passengers being assessed as low risk. The recall rate for medium-risk passengers reached 96%, with only 2% of medium-risk passengers assessed as low risk. The recall rate for low-risk passengers also reached 96%, with no low-risk passengers assessed as high risk. The proposed method enables a dynamic quantification assessment of civil aviation passenger risks, effectively integrating expert knowledge and indicator characteristics. This provides a theoretical foundation for a more comprehensive, rational, and scientifically-driven analysis of risks associated with civil aviation passengers.